Objective : To investigate the prevalence of dyslipidemia among overweight and obese primary and middle school students in Tongzhou District, so as to provide the evidence for the implementation of comprehensive health education and early interventions for overweight and obese students. Methods : The basic information, physical examinations and blood lipid testing results were collected from the primary and middle school students in Tongzhou District from 2015 to 2019 through the nutrition and health monitoring project among students in Tongzhou District. The epidemiological characteristics of overweight and obese students with dyslipidemia were descriptively analyzed. Results : Among the 1 483 primary and middle school students detected, the overall prevalence rates of overweight, obesity and dyslipidemia were 12.68% ( 188 students ), 20.43% ( 303 students ) and 20.57% ( 305 students ), respectively. The prevalence of dyslipidemia was higher in overweight and obese students ( 24.44% ) than in students with normal weight ( 18.65%, P<0.05 ), and the prevalence of dyslipidemia was higher in male overweight and obese students than in female overweight and obese students (29.00% vs. 18.92%, P<0.05), while higher prevalence of dyslipidemia was seen in middle school students than in primary school students ( 37.72% vs. 20.32%, P<0.05 ). In addition, the prevalence of dyslipidemia was higher in students with daily exercise of less than a hour than in students with daily exercise of a hour or longer ( 27.88% vs. 18.44%, P<0.05 ). Conclusions The prevalence of dyslipidemia is high among overweight and obese primary and middle school students in Tongzhou District. Health educations should be reinforced to male, middle school students with daily exercise of less than a hour.

Under the backdrop of smart health management technology development, this article reviews research advances in smart monitoring, assessment and intervention technologies for older people with mild cognitive impairment, including the types, typical applications and results of monitoring, assessment and intervention technologies.In addition, from the perspective of community-dwelling older adults' cognitive health management, a model for innovative management of community-dwelling older adults' cognitive function taking advantage of smart health management technologies is proposed, aiming to enhance the acceptance of smart health technologies among older people with cognitive impairment and to provide policy advice on developing friendly communities for older people with cognitive impairment.

Objective: To explore the screen related sedentary behavior among senior primary school students in Beijing and to analyze the influence of psychosocial determinants and nutrition related knowledge on the behavior. Methods: In January 2020, a total of 1 316 students in grade 4-6 from two primary schools in Beijing were selected. Information on video viewing (watching TV or playing video games), self efficacy, habit strength, nutrition related knowledge, outcome expectation and the capacity to persist toward goal attainment were collected through questionnaires. Disordered multi classification Logistic regression and random forest algorithm were used to analyze the influencing factors. Results: The frequency of screen related sedentary was 5.0 (3.0, 10.5) times/week, and the duration was 37.5(9.6, 97.5) min/d in senior elementary school children. The results of disordered multi classification Logistic regression showed that the capacity to persist toward goal attainment, nutrition related knowledge, habit strength, self efficacy and gender positively correlated with the frequency of screen related sedentary ( OR =1.6, 1.7, 4.9, 4.2, 1.5 ), while the nutrition related knowledge, habit strength, self efficacy, outcome expectations, grade and gender positively correlated with screen time ( OR =1.7, 5.6, 5.7, 1.6, 1.6, 1.7)( P <0.05). Random forest regression tree model showed that the top four influencing factors on screen related sedentary frequency were self efficacy, the capacity to persist toward goal attainment, habit strength and nutrition related knowledge and the top four influencing factors on screen time were self efficacy, outcome expectation, nutrition related knowledge, habit strength. Conclusion Screen related sedentary behavior is prevalent among senior primary school students in Beijing. Health education should be strengthened regarding influencing factors of screen related sedentary behavior.

Objective: The association of self efficacy, habit strength, goal intention and outcome expectation with the consumption of snack in senior primary school students were investigated, providing evidence for the application of psychosocial determinants based on Social Cognitive Theory in children s nutrition education. Methods: A total of 1 353 students, 10-12 years old, participated in this study. Participants completed questionnaires for assessing self efficacy, habit strength, goal intention, outcome expectation and snack consumption in January 2020. Results: Average times of snack consumption among primary school students were 5.0 (3.0, 8.5) times per week, and the snack intake were 4.0(0.9, 22.9)g/d. The outcome expectation score was -1.0(-2.0, -1.0 ) points, while the score of children s snack related selfefficacy was (4.3±0.9) points, habit strength score 1.0(1.0, 3.0) points, and the goal intention (4.2±1.2) points. Students with higher snack intake showed lower scores in outcome expectation, self efficacy and goal intention( t=-9.0, 6.8, 5.2, P <0.01). Logistic regression showed negative association between outcome expectation and self efficacy factors with snacking behavior( OR =0.7, 0.8, respectively), as well as positive association between habit strength and snacking behaviors( OR=1.3, P <0.05). Conclusion The evidence indicated that self efficacy, habit strength, goal intention and outcome expectation are associated with child s snack consumption, and can be used as theoretical foundation for child snack consumption education.

Objective: To analyze the incidence rate of occupational noise-induced hearing loss in noise-exposed workers in an iron and steel plant from 2006 to 2015. Methods: Using a cohort study method, workers exposed to occupational noise from Jan 1, 2006 to Dec 12, 2015 were followed up and the pure tone hearing test was conducted. In total, 6 297 subjects completed two or more physical checks and the pure tone hearing test and were included in the analysis. The noise exposure level at the workplace and the equivalent continuous A-weighted sound pressure level for workers was monitored and the cumulative noise exposure dose was evaluated. The subjects were divided into low, middle and high exposure groups according to the noise exposure level, and the equivalent continuous A-weighted sound pressure level for 8 hours for each group was 80.6-85.0, 85.1-90.0 and 90.1-103.4 dB (A), respectively. While the RR and 95% CI were derived from unconditional logistic regression models. In logistic regression analysis, confounding factors such as age, gender, smoking habit, drinking habit, high temperature exposure and chemical hazards exposure level were controlled. Results: During the follow-up period, 392 cases of occupational noise-induced hearing loss were diagnosed among the 6 297 subjects, with an incidence rate of 6.23%; 318 cases of high-frequency hearing loss were diagnosed, with an incidence rate of 5.05%; and 74 cases of occupational noise-induced deafness were diagnosed, with an incidence rate of 1.18% . The incidence rates of hearing loss among the high, medium and low exposure groups were 9.22% (158/1 737), 6.49% (204/3 142) and 2.08% (30/1 442), respectively; the rates of high-frequency hearing loss were 7.41% (127/1 737), 5.25% (165/3 142) and 1.80% (26/1 442), respectively; and the rates of occupational noise-induced deafness were 1.81% (31/1 737), 1.24% (39/3 142) and 0.28% (4/1 442), respectively. For the groups corresponding to cumulative noise exposure doses of ≤84.99, 85.00- 87.99, 88.00- 90.99, 91.00- 93.99, 94.00- 96.99, 97.00- 100.99, 101.00- 102.99 and ≥103.00 dB (A) · year, the incidence rates of hearing loss were 0 (0/185), 1.22% (2/164), 2.52% (17/674), 3.83% (35/913), 5.80% (106/1 827), 6.02% (67/1 113), 9.20% (95/1 003) and 18.04% (70/388), respectively. Compared with the low exposure group, the RR of hearing loss, high-frequency hearing loss and occupational noise-induced deafness for the high exposure group were 4.78 (95% CI: 3.22- 7.11), 4.36 (95% CI: 2.84- 6.69) and 6.63 (95% CI: 2.33- 18.82), respectively; and for the medium exposure group were 3.27 (95% CI: 2.22-4.82), 3.02 (95% CI: 1.99-4.59) and 4.52 (95% CI: 1.61-12.67), respectively. Conclusion The incidence rate of hearing loss for workers exposed to noise in an iron and steel plant was related to the cumulative noise exposure dose, gender, age, educational level, smoking habits, drinking habits and exposure to high temperature.

Objective: The aim of this study was to investigate whether genetic variability in the protocadherin 15 (PCDH15) gene may correspond with increased susceptibility to noise-induced hearing loss (NIHL) in a Chinese population. Methods: A nested case-control study was performed that followed a cohort of 7 445 noise-exposed workers in a steel factory of Henan province in China from January 1, 2006 to December 31, 2015. In this study, 394 cases who had an average hearing threshold of more than 40 dB (A) in high frequency were defined as the case group, and 721 controls who had an average hearing threshold of less than 35 dB (A) in high frequency and less than 25 dB (A) in speech frequency were defined as the control group. A questionnaire was completed by participants and a physical test was also conducted. SNP genotyping was performed using the SNPscan^TM Kit. Multivariate unconditional logistic regression additive models were used to analyze the genotypes in different groups, and the association with NIHL. Unconditional logistic regression models were used to assess the associations between the genotypes and NIHL. Results: The average age of study participants was (40.5±8.3) years and the median number of noise-exposed working years M (P₂₅, P₇₅) was 21.1 (9.1, 27.3). The range of noise exposed levels and the levels of cumulative noise exposure (CNE) were 80.1- 98.8 dB(A) and 86.6- 111.2 dB(A), respectively. Only the distribution of the genotypes (TT/CC/CT) of rs11004085 in the PCDH15 gene showed a significant difference between the case and control groups (P=0.049). In the case group, the distribution was 370 (93.9%), 24 (6.1%) and 0; in the control group, the distribution was 694 (96.3%), 23 (3.2%) and 1 (0.1% ). After smoking, drinking, hypertension, height and CNE adjustment, compared with the TT genotype individuals with the CC/CT genotype had a 1.90-fold increased risk of NIHL (95% CI: 1.06- 3.40). After stratified these data by the noise exposure level or CNE when the noise exposure level was>85 dB (A), compared with cases with the AA genotype of rs10825113, individuals with the GA/GG genotype had a 2.63-fold increased risk of NIHL (95% CI: 1.12- 6.14). When the CNE was ≤ 98 dB(A), compared with cases with the TT genotype of rs11004085, individuals with the CC/CT genotype had a 2.96-fold increased risk of NIHL (95% CI: 1.33- 6.56). However, these differences were not significant after Bonferroni correction had been applied. Conclusions The results confirmed that genetic variation within the PCDH15 gene may affect the susceptibility to NIHL.

Objective: To identify the association between genetic polymorphisms in the eye absent homolog 4 (EYA4) gene and noise-induced hearing loss (NIHL). Method: A nested case control study was conducted based on a cohort of noise-exposed subjects. In total, 292 cases were selected from a steel factory from 6 297 subjects during Jan 1, 2006 to Dec 12, 2015,who had an average hearing threshold of more than 40 dB(A); 584 matched control subjects for each case were designated on the basis of matched criteria including same gender, age (±5 years) and duration of exposure to noise (±2 years). What's more, the control group had an average hearing threshold of less than 35 dB(A) in high frequency and less than 25 dB(A) in speech frequency. Four single nucleotide polymorphisms (SNPs) of the EYA4 gene were genotyped using a SNPscan^TM multiplex SNP genotyping kit. Hardy-Weinberg equilibrium tests were performed using a χ² test for goodness-of-fit for each SNP among the control group, and the effects of genotypes of the EYA4 gene on NIHL were analyzed by logistic regression. The haplotypes were established and their frequencies in the two groups were assessed using Haploview 4.2 and Phase 2.1 software, and interactive effects between haplotypes and cumulative noise exposure were analyzed. Results: The average age of the subjects was (40.1±8.4) years and the average number of noise-exposed working years was 20.3 (8.4, 27.3) years. The range of noise exposure levels and the cumulative noise exposure were 80.2- 98.8 dB (A) and 86.6- 111.2 dB(A) · year, respectively. After adjustment for covariates including height, blood pressure, drinking status and smoking status, in the noise intensity>85 dB (A) group, subjects carrying the rs3813346 TT genotype had a higher NIHL risk than those carrying the GG genotype, and the adjusted OR (95% CI) value was 2.12 (1.21- 3.69). In the cumulative noise exposure>98 dB (A) · year group, compared with haplotype TGC, haplotype CGT showed a protective effect in the development of NIHL, with an adjusted OR (95% CI) value of 0.60 (0.37-0.97), however, the significance of intercation between EY4 gene of noise was lost after Bonferroni correction. Conclusion Genetic polymorphism in the EYA4 gene may be a genetic susceptibility factor for NIHL.

Objective: To explore the relationship between mitochondrial 12 S rRNA gene variation, tRNA gene variation and cytochrome oxidase Ⅱ gene point mutations and the risk of noise-induced hearing loss (NIHL). Methods: A nested case-control study was performed that followed a cohort of 7 445 noise-exposed workers in a steel factory in Henan province, China, from January 1, 2006 to December 31, 2015. Subjects whose average hearing threshold was more than 40 dB(A) in high frequency were defined as the case group, and subjects whose average hearing threshold was less than 35 dB(A) in high frequency and less than 25 dB (A) in speech frequency were defined as the control group. Subjects was recruited into the case group (n=286) and the control group (n=286) according to gender, age, job category and time of exposure to noise, and a 1∶1 case-control study was carried out. We genotyped eight single nucleotide polymorphisms in the mitochondrial 12 S rRNA gene, the mitochondrial tRNA gene and the mitochondrial cytochrome oxidase Ⅱ gene using SNPscan high-throughput genotyping technology from the recruited subjects. The relationship between polymorphic sites and NIHL, adjusted for covariates, was analyzed using conditional logistic regression analysis, as were the subgroup data. Results: The average age of the recruited subjects was (40.3±8.1) years and the length of service exposure to noise was (18.6±8.9) years. The range of noise exposed levels and cumulative noise exposure (CNE) was 80.1- 93.4 dB (A) and 86.8- 107.9 dB (A) · year, respectively. For workers exposed to noise at a CNE level<98 dB (A) · year, smokers showed an increased risk of NIHL of 1.88 (1.16-3.05) compared with non-smokers; for workers exposed to noise at a CNE level ≥98 dB(A) · year, smokers showed an increased risk of NIHL of 2.53 (1.49- 4.30) compared with non-smokers. For workers exposed to noise at a CNE level<98 dB (A) · year, the results of univariate analysis and multifactor analysis, adjusted by smoking and CNE, suggested that the risk of NIHL in workers exposed to noise carrying the GG genotype (G827A) was lower than that of NIHL workers exposed to noise carrying the AA genotype (G827A) [OR (95% CI) were 0.18 (0.04- 0.82) and 0.19 (0.04- 0.88), respectively]. Conclusion Smoking increased the risk of NIHL in the present study. For workers subjected to a CNE<98 dB(A)·year, the mitochondrial genetic variant G827A was found to be significantly associated with the risk of NIHL.